IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i24p9401-d1001078.html
   My bibliography  Save this article

Optimal Dispatch of Regional Integrated Energy System Group including Power to Gas Based on Energy Hub

Author

Listed:
  • Zhilin Lyu

    (College of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Quan Liu

    (College of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Bin Liu

    (College of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Lijun Zheng

    (State Grid Zhangjiajie Power Supply Company, Zhangjiajie 427000, China)

  • Jiaqi Yi

    (College of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Yongfa Lai

    (College of Electrical Engineering, Guangxi University, Nanning 530004, China)

Abstract

Different renewable energy resources and energy demands between parks lead to waste of resources and frequent interactions between the regional distribution grid and the larger grid. Hence, an optimal dispatching scheme of the regional integrated energy system group (RIESG), which combines the power-to-gas (P2G) and inter-park electric energy mutual aid, is proposed in this paper to solve this problem. Firstly, for the park integrated energy system (PIES) with various structures, the coupling matrix is used to describe the input-output relationship and coupling form of multiple energy sources in the energy-hub (EH), which linearizes the complex multi-energy coupled system and is more conducive to the solution of the model. Secondly, the electrical coupling relationship of the system is improved by adding P2G to enhance the system’s ability to consume renewable energy. Moreover, the installation cost of P2G is introduced to comprehensively consider the impact of the economic efficiency on the system. Finally, to minimize the network loss of energy flow, the optimal dispatching model of RIESG with P2G conversion is constructed through the electric energy mutual aid among the parks. The simulation shows that compared with the independent operation of each park’s integrated energy system (IES), the proposed optimal dispatching strategy of RIESG achieves the mutual benefit of electric energy among park groups, reduces the dependency on the large power grid, and effectively improves the economy of system groups. In this condition, the renewable energy consumption rate reaches 99.59%, the utilization rate of P2G increases to 94.28%, and the total system cost is reduced by 34.83%.

Suggested Citation

  • Zhilin Lyu & Quan Liu & Bin Liu & Lijun Zheng & Jiaqi Yi & Yongfa Lai, 2022. "Optimal Dispatch of Regional Integrated Energy System Group including Power to Gas Based on Energy Hub," Energies, MDPI, vol. 15(24), pages 1-22, December.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:24:p:9401-:d:1001078
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/24/9401/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/24/9401/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Huiru Zhao & Hao Lu & Xuejie Wang & Bingkang Li & Yuwei Wang & Pei Liu & Zhao Ma, 2020. "Research on Comprehensive Value of Electrical Energy Storage in CCHP Microgrid with Renewable Energy Based on Robust Optimization," Energies, MDPI, vol. 13(24), pages 1-22, December.
    2. Fambri, Gabriele & Diaz-Londono, Cesar & Mazza, Andrea & Badami, Marco & Sihvonen, Teemu & Weiss, Robert, 2022. "Techno-economic analysis of Power-to-Gas plants in a gas and electricity distribution network system with high renewable energy penetration," Applied Energy, Elsevier, vol. 312(C).
    3. Andrade, Carlos & Selosse, Sandrine & Maïzi, Nadia, 2022. "The role of power-to-gas in the integration of variable renewables," Applied Energy, Elsevier, vol. 313(C).
    4. Majed A. Alotaibi & Ali M. Eltamaly, 2021. "A Smart Strategy for Sizing of Hybrid Renewable Energy System to Supply Remote Loads in Saudi Arabia," Energies, MDPI, vol. 14(21), pages 1-24, October.
    5. Majed A. Alotaibi & Ali M. Eltamaly, 2022. "Upgrading Conventional Power System for Accommodating Electric Vehicle through Demand Side Management and V2G Concepts," Energies, MDPI, vol. 15(18), pages 1-27, September.
    6. Wang, Haixin & Yang, Junyou & Chen, Zhe & Li, Gen & Liang, Jun & Ma, Yiming & Dong, Henan & Ji, Huichao & Feng, Jiawei, 2020. "Optimal dispatch based on prediction of distributed electric heating storages in combined electricity and heat networks," Applied Energy, Elsevier, vol. 267(C).
    7. Li, Li & Wang, Jing & Zhong, Xiaoyi & Lin, Jian & Wu, Nianyuan & Zhang, Zhihui & Meng, Chao & Wang, Xiaonan & Shah, Nilay & Brandon, Nigel & Xie, Shan & Zhao, Yingru, 2022. "Combined multi-objective optimization and agent-based modeling for a 100% renewable island energy system considering power-to-gas technology and extreme weather conditions," Applied Energy, Elsevier, vol. 308(C).
    8. Bloess, Andreas, 2020. "Modeling of combined heat and power generation in the context of increasing renewable energy penetration," Applied Energy, Elsevier, vol. 267(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. He, Zhaoyu & Guo, Weimin & Zhang, Peng, 2022. "Performance prediction, optimal design and operational control of thermal energy storage using artificial intelligence methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    2. Jiang, Kai & Yan, Xiaohe & Liu, Nian & Wang, Peng, 2022. "Energy trade-offs in coupled ICM and electricity market under dynamic carbon emission intensity," Energy, Elsevier, vol. 260(C).
    3. Jiaan Zhang & Chenyu Liu & Leijiao Ge, 2022. "Short-Term Load Forecasting Model of Electric Vehicle Charging Load Based on MCCNN-TCN," Energies, MDPI, vol. 15(7), pages 1-25, April.
    4. Han, Fengwu & Zeng, Jianfeng & Lin, Junjie & Zhao, Yunlong & Gao, Chong, 2023. "A stochastic hierarchical optimization and revenue allocation approach for multi-regional integrated energy systems based on cooperative games," Applied Energy, Elsevier, vol. 350(C).
    5. Ji, Huichao & Wang, Haixin & Yang, Junyou & Feng, Jiawei & Yang, Yongyue & Okoye, Martin Onyeka, 2021. "Optimal schedule of solid electric thermal storage considering consumer behavior characteristics in combined electricity and heat networks," Energy, Elsevier, vol. 234(C).
    6. Benjamin Kwaku Nimako & Silvia Carpitella & Andrea Menapace, 2024. "Novel Multi-Criteria Decision Analysis Based on Performance Indicators for Urban Energy System Planning," Energies, MDPI, vol. 17(20), pages 1-18, October.
    7. Ebrahimi-Moghadam, Amir & Farzaneh-Gord, Mahmood, 2022. "Optimal operation of a multi-generation district energy hub based on electrical, heating, and cooling demands and hydrogen production," Applied Energy, Elsevier, vol. 309(C).
    8. Víctor Sanz i López & Ramon Costa-Castelló & Carles Batlle, 2022. "Literature Review of Energy Management in Combined Heat and Power Systems Based on High-Temperature Proton Exchange Membrane Fuel Cells for Residential Comfort Applications," Energies, MDPI, vol. 15(17), pages 1-22, September.
    9. He, Yi & Guo, Su & Zhou, Jianxu & Wu, Feng & Huang, Jing & Pei, Huanjin, 2021. "The many-objective optimal design of renewable energy cogeneration system," Energy, Elsevier, vol. 234(C).
    10. Ma, Huan & Chen, Qun & Hu, Bo & Sun, Qinhan & Li, Tie & Wang, Shunjiang, 2021. "A compact model to coordinate flexibility and efficiency for decomposed scheduling of integrated energy system," Applied Energy, Elsevier, vol. 285(C).
    11. Liwen Zhu & Jun He & Lixun He & Wentao Huang & Yanyang Wang & Zong Liu, 2022. "Optimal Operation Strategy of PV-Charging-Hydrogenation Composite Energy Station Considering Demand Response," Energies, MDPI, vol. 15(16), pages 1-23, August.
    12. Chang, Miguel & Lund, Henrik & Thellufsen, Jakob Zinck & Østergaard, Poul Alberg, 2023. "Perspectives on purpose-driven coupling of energy system models," Energy, Elsevier, vol. 265(C).
    13. Arkadiusz Dobrzycki & Jacek Roman, 2022. "Correlation between the Production of Electricity by Offshore Wind Farms and the Demand for Electricity in Polish Conditions," Energies, MDPI, vol. 15(10), pages 1-18, May.
    14. Xu, Jiazhu & Yi, Yuqin, 2023. "Multi-microgrid low-carbon economy operation strategy considering both source and load uncertainty: A Nash bargaining approach," Energy, Elsevier, vol. 263(PB).
    15. Haibing Wang & Chengmin Wang & Weiqing Sun & Muhammad Qasim Khan, 2022. "Energy Pricing and Management for the Integrated Energy Service Provider: A Stochastic Stackelberg Game Approach," Energies, MDPI, vol. 15(19), pages 1-15, October.
    16. Shen, Xiaojun & Li, Xingyi & Yuan, Jiahai & Jin, Yu, 2022. "A hydrogen-based zero-carbon microgrid demonstration in renewable-rich remote areas: System design and economic feasibility," Applied Energy, Elsevier, vol. 326(C).
    17. Pastore, Lorenzo Mario & Lo Basso, Gianluigi & Ricciardi, Guido & de Santoli, Livio, 2022. "Synergies between Power-to-Heat and Power-to-Gas in renewable energy communities," Renewable Energy, Elsevier, vol. 198(C), pages 1383-1397.
    18. Liu, Fan & Duan, Jiandong & Wu, Chen & Tian, Qinxing, 2024. "Risk-averse distributed optimization for integrated electricity-gas systems considering uncertainties of Wind-PV and power-to-gas," Renewable Energy, Elsevier, vol. 227(C).
    19. Yang, Yu & Liu, Zhiqiang & Xie, Nan & Wang, Jiaqiang & Cui, Yanping & Agbodjan, Yawovi Souley, 2023. "Multi-criteria optimization of multi-energy complementary systems considering reliability, economic and environmental effects," Energy, Elsevier, vol. 269(C).
    20. Zheng, Shunlin & Qi, Qi & Sun, Yi & Ai, Xin, 2023. "Integrated demand response considering substitute effect and time-varying response characteristics under incomplete information," Applied Energy, Elsevier, vol. 333(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:24:p:9401-:d:1001078. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.